License

This Matlab tutorial demonstrates step by step the single-channel version of a singular spectrum analysis (SSA), a nonparametric spectral estimation method for time series. The guide explains the following steps of an SSA analysis
- creation of the trajectory matrix
- calculation of the covariance matrix
- eigendecomposition of the covariance matrix
- resulting eigenvalues, eigenvectors
- calculation of the principal components
- reconstruction of the time series.
The tutorial also explains the difference between the Toeplitz approach of Vautard and Ghil (1989) and the trajectory approach of Broomhead and King (1986). Note that only the latter approach ensures a positive semi-definite covariance matrix with non-negative eigenvalues. For a review of SSA see Ghil et al. (2002) and Groth and Ghil (2015).
References